few-shot-gan-adaptation Official repository for Few-shot Image Generation via Cross-domain Correspondence (CVPR ’21) Utkarsh Ojha, Yijun Li, Jingwan Lu, Alexei A. Efros, Yong Jae Lee, Eli Shechtman, Richard Zhang Adobe Research, UC Davis, UC Berkeley Repository for downloading the datasets and generated images used for performing the evaluations shown in Tables 1 and 2. Overview Our method helps adapt the source GAN where one-to-one correspondence is preserved between the source Gs(z) and target Gt(z) images. Sample images from a model To […]

Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. Getting Started Getting up and running with Metaflow is easy. Python Install metaflow from pypi: pip install metaflow and access tutorials by typing: metaflow tutorials pull R Install Metaflow from github: devtools::install_github(“Netflix/metaflow”, subdir=”R”) metaflow::install() and […]

ODMD Dataset ODMD is the first dataset for learning Object Depth via Motion and Detection. ODMD training data are configurable and extensible, with each training example consisting of a series of object detection bounding boxes, camera movement distances, and ground truth object depth. As a benchmark evaluation, we provide four ODMD validation and test sets with 21,600 examples in multiple domains, and we also convert 15,650 examples from the ODMS benchmark for detection. In our paper, we use a single […]

YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Setup If you are going to train the model on Google Colab, you could skip this section and jump straight to Training on Google Colab. Otherwise, to run training locally, you need to have a x86_64 PC with a decent GPU. For example, I mainly test the code in this repository using a desktop PC with: NVIDIA GeForce RTX […]

MIDASpy MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant accuracy and efficiency advantages over other multiple imputation strategies, particularly when applied to large datasets with complex features. In addition to implementing the algorithm, the package contains functions for processing data before and after model training, running imputation model diagnostics, generating multiple completed datasets, and estimating regression models on these datasets. Background and suggested citation For more information on MIDAS, […]

Python-Fast-Raytracer A basic Ray Tracer that exploits numpy arrays and functions to work fast. The code is written keeping as much readability as possible. [x] Refraction [x] Thin film interference [x] Textures [x] Monte Carlo Ray Tracing with importance sampling [ ] Relativistic optical effects Installation Just clone or download this repo. You’ll need to install two packages. Pillow is a fork of the PIL package. It provides the Image module for this application.to install it run the following. pip […]

spatial-intention-maps Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser IEEE International Conference on Robotics and Automation (ICRA), 2021 Abstract: The ability to communicate intention enables decentralized multi-agent robots to collaborate while performing physical tasks. In this work, we present spatial intention maps, a new intention representation for multi-agent vision-based deep reinforcement learning that improves coordination between decentralized mobile manipulators. In this representation, each agent’s intention is provided to other agents, and rendered into an overhead 2D […]

Random Face A simple python library for fast image generation of people who do not exist. Requirements Linux, Windows, MacOS Python 3.8+ CPU compatible with OpenVINO. Install package pip install random_face Install the latest version git clone https://github.com/bes-dev/random_face.git cd random_face pip install -r requirements.txt python download_model.py pip install . Demo python -m random_face.demo Example import cv2 import random_face engine = random_face.get_engine() face = engine.get_random_face() cv2.imshow(“face”, face) cv2.waitKey() Citation @misc{belousov2021mobilestylegan, title={MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis}, author={Sergei […]

QPIC Repo for CVPR2021 paper “QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information” by Masato Tamura, Hiroki Ohashi, and Tomoaki Yoshinaga. QPIC is implemented by extending the recently proposed object detector, DETR. QPIC leverages the query-based detection and attention mechanism in the transformer, and as a result, achieves high HOI detection performance with simple detection heads. Example attention maps. Preparation Dependencies Our implementation uses external libraries such as NumPy and PyTorch. You can resolve the dependencies with the […]

pybullet-planning (ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and motion planning (TAMP). This repository was originally developed for the PDDLStream (previously named STRIPStream) approach to TAMP. With the help of Yijiang Huang, a stable and documented fork of ss-pybullet named pybullet_planning is available through PyPI. However, new features will continue to be introduced first through ss-pybullet. Installation Install PyBullet on OS X or Linux using: $ pip install numpy pybullet $ git […]